Generative AI Application Integration Patterns : Integrate Large Language Models into Your Applications

Generative AI Application Integration Patterns Integrate Large Language Models into Your Applications

Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, depl...

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Detalles Bibliográficos
Otros Autores: Bustos, Juan Pablo, author (author), Soria, Luis Lopez, author (writer of foreword), Arsanjani, Ali, writer of foreword
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited 2024.
Colección:Expert insight.
Materias:
Artificial intelligence.
Application software > Development.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009847338606719
Tabla de Contenidos:
  • Cover
  • Copyright
  • Foreword
  • Contributors
  • Table of Contents
  • Preface
  • Chapter 1: Introduction to Generative AI Patterns
  • From AI predictions to generative AI
  • Predictive AI vs generative AI use case ideation
  • A change in the paradigm
  • Predictive AI use case development
  • simplified lifecycle
  • Generative AI use case development
  • simplified lifecycle
  • General generative AI concepts
  • Generative AI model architectures
  • Techniques available to optimize foundational models
  • Techniques to augment your foundational model responses
  • Constant evolution across the generative AI space
  • Introducing generative AI integration patterns
  • Summary
  • Chapter 2: Identifying Generative AI Use Cases
  • When to consider generative AI
  • Realizing business value
  • Identifying Generative AI use cases
  • Potential business-focused use cases
  • Generative AI deployment and hosting options
  • Summary
  • Chapter 3: Designing Patterns for Interacting with Generative AI
  • Defining an integration framework
  • Entry point
  • Prompt pre-processing
  • Inference
  • Results post-processing
  • Selecting from amongst multiple outputs
  • Refining generated outputs
  • Results presentation
  • Logging
  • Summary
  • Chapter 4: Generative AI Batch and Real-Time Integration Patterns
  • Batch and real-time integration patterns
  • Different pipeline architectures
  • Application integration patterns in the integration framework
  • Entry point
  • Prompt preprocessing
  • Inference
  • Result post-processing
  • Result presentation
  • Use case example
  • search enhanced by GenAI
  • Batch integration
  • document ingestion
  • Real-time integration
  • search
  • Summary
  • Chapter 5: Integration Pattern: Batch Metadata Extraction
  • Use case definition
  • Architecture
  • Entry point
  • Prompt pre-processing
  • Inference
  • Result post-processing
  • Result presentation
  • Summary
  • Chapter 6: Integration Pattern: Batch Summarization
  • Use case definition
  • Architecture
  • Entry point
  • Prompt preprocessing
  • Inference
  • Result post-processing
  • Result presentation
  • Summary
  • Chapter 7: Integration Pattern: Real-Time Intent Classification
  • Use case definition
  • Architecture
  • Entry point
  • Prompt pre-processing
  • Inference
  • Result post-processing
  • Result presentation
  • Logging and monitoring
  • Summary
  • Chapter 8: Integration Pattern: Real-Time Retrieval Augmented Generation
  • Use case definition
  • Architecture
  • Entry point
  • Prompt preprocessing
  • Inference
  • Result post-processing
  • Result presentation
  • Use case demo
  • The Gradio app
  • Summary
  • Chapter 9: Operationalizing Generative AI Integration Patterns
  • Operationalization framework
  • Data layer
  • A real-world example: Part 1
  • Training layer
  • A real-world example: Part 2
  • Inference layer
  • A real-world example: Part 3
  • Operations layer
  • CI/CD and MLOps
  • Monitoring and observability
  • Evaluation and monitoring

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